Llama-3.3-70B-Instruct vs Mistral Small 3.1 24B vs Mixtral 8x7B
Mistral Small 3.1 24B comes out ahead, 55 to 46 and 37 on our weighted score, and it is the cheaper option too.
MetaLlama-3.3-70B-Instruct
46/100- ECI127.3
- Price$0.59 / $0.724
- Context128K
- Our pick
Mistral AIMistral Small 3.1 24B
55/100- ECI127.5
- Price$0.229 / $0.436
- Context128K
- Mistral AI
Mixtral 8x7B
37/100- ECI118.5
- Price$0.70 / $0.70
- Context32K
Mistral Small 3.1 24B is our pick
Mistral Small 3.1 24B is the better all-round choice, scoring 55/100 against Llama-3.3-70B-Instruct (46) and Mixtral 8x7B (37). It leads on price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityMistral Small 3.1 24BCapabilities Index (ECI): Mistral Small 3.1 24B 127.5 · Llama-3.3-70B-Instruct 127.3 · Mixtral 8x7B 118.5
- Lowest priceMistral Small 3.1 24BMistral Small 3.1 24B $0.281 · Llama-3.3-70B-Instruct $0.624 · Mixtral 8x7B $0.70 per 1M tokens (3:1 blend)
- Longest contextLlama-3.3-70B-Instruct and Mistral Small 3.1 24BLlama-3.3-70B-Instruct 128,000 · Mistral Small 3.1 24B 128,000 · Mixtral 8x7B 32,000 tokens
- Widest inputsMistral Small 3.1 24BLlama-3.3-70B-Instruct: Text · Mistral Small 3.1 24B: Text, Images · Mixtral 8x7B: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Llama-3.3-70B-Instruct | Mistral Small 3.1 24B | Mixtral 8x7B |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 49 | 50 | 38 |
| Price | 25% | 60 | 76 | 57 |
| Inputs & features | 15% | 25 | 60 | 25 |
| Context window | 10% | 24 | 24 | 0 |
| Overall | 100% | 46/100 | 55/100 | 37/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Llama-3.3-70B-InstructMeta | Mistral Small 3.1 24BMistral AI | Mixtral 8x7BMistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 127.3 | 127.5 (best) | 118.5 |
| ECI rank | #133 of 148 | #132 of 148 (best) | #142 of 148 |
| GPQA DiamondGraduate-level science questions | 47.4% | 47.5% (best) | 30.6% |
| OTIS Mock AIME 2024–2025Competition mathematics | 5.1% | 5.8% (best) | — |
| Price per million tokens | |||
| Input | $0.59 | $0.229 (best) | $0.70 |
| Output | $0.724 | $0.436 (best) | $0.70 |
| Cached input | — | — | — |
| Blended (3:1) | $0.624 | $0.281 (best) | $0.70 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 21 providers | Median of 2 providers | Official Mistral API |
| Limits | |||
| Context window | 128,000 tokens (best) | 128,000 tokens (best) | 32,000 tokens |
| Max output | 4,096 tokens | 16,384 tokens | 32,000 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Open | Open |
| API model ID | llama-3.3-70b-instruct | — | open-mixtral-8x7b |
| API providers | 24 (best) | 2 | 1 |
| Released | Dec 6, 2024 | Mar 17, 2025 | Dec 11, 2023 |
| Knowledge cutoff | Dec 2023 | Jun 2024 | Jan 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Llama-3.3-70B-Instruct$7.35
- Mistral Small 3.1 24B$3.16
- Mixtral 8x7B$8.40
Which should you choose?
Which is better: Llama-3.3-70B-Instruct, Mistral Small 3.1 24B or Mixtral 8x7B?
Mistral Small 3.1 24B is the better all-round choice, scoring 55/100 against Llama-3.3-70B-Instruct (46) and Mixtral 8x7B (37). It leads on price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Llama-3.3-70B-Instruct, Mistral Small 3.1 24B or Mixtral 8x7B?
Mistral Small 3.1 24B is cheaper at $0.229 input / $0.436 output per million tokens (median across 2 API providers). Llama-3.3-70B-Instruct costs $0.59 input / $0.724 output per million tokens (median across 21 API providers; free on Llama); Mixtral 8x7B costs $0.70 input / $0.70 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.281 per million tokens for Mistral Small 3.1 24B versus $0.624 for Llama-3.3-70B-Instruct (2.2× as much) and $0.70 for Mixtral 8x7B (2.5× as much).
Which scores higher on benchmarks?
Mistral Small 3.1 24B scores higher on the Capabilities Index (ECI): Mistral Small 3.1 24B 127.5 (#132 of 148), Llama-3.3-70B-Instruct 127.3 (#133 of 148) and Mixtral 8x7B 118.5 (#142 of 148). The confidence ranges of the top two overlap (122.6–129.4 vs 122.5–129.5), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Small 3.1 24B 47.5%, Llama-3.3-70B-Instruct 47.4%, Mixtral 8x7B 30.6%.
Which is better for coding?
There are no published SWE-bench Verified results for Llama-3.3-70B-Instruct, Mistral Small 3.1 24B and Mixtral 8x7B yet, so there is no like-for-like coding score. On overall capability, Mistral Small 3.1 24B leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
Llama-3.3-70B-Instruct and Mistral Small 3.1 24B have the largest context windows (128,000 and 128,000 tokens), against 32,000 for Mixtral 8x7B. Maximum output per response: Llama-3.3-70B-Instruct up to 4,096, Mistral Small 3.1 24B up to 16,384, Mixtral 8x7B up to 32,000 tokens.
Which can read images, PDFs, audio or video?
Llama-3.3-70B-Instruct accepts text; Mistral Small 3.1 24B accepts text and images; Mixtral 8x7B accepts text. Mistral Small 3.1 24B handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights, so you can self-host them.
Which is newer?
Mistral Small 3.1 24B is the newest, released Mar 17, 2025. Llama-3.3-70B-Instruct came out Dec 6, 2024; Mixtral 8x7B came out Dec 11, 2023. Knowledge cutoff: Llama-3.3-70B-Instruct Dec 2023, Mistral Small 3.1 24B Jun 2024, Mixtral 8x7B Jan 2024.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
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